Video data is generally processed and transferred in the form of bitstreams. A bitstream is spatially scalable if the bitstream contains at least one independently decodable substream representing video sequence which is less than the full resolution of the bitstream. The conventional standards for processing video data, such as Moving Pictures Experts Group (MPEG) 2, MPEG 4 and H.263+ standards, include spatial scalability modes.
There have been some problems and difficulties in processing video data using the conventional standards. For example, video data processing for spatially scalable video data is inefficient because decoded enhancement-layer sequence has significantly lower video quality than a non-scalable sequence at the same bit rate.
One improved scheme over the conventional video data processing systems and methods is a discrete cosine transform (DCT)-based subband decomposition approach in which subband decomposition is used to create base and enhancement layer data which are then encoded using motion compensated DCT coding. The DCT-based subband decomposition approach is more completely described in “Spatial scalable video coding using a combined subband-DCT approach”, by U. Benzler, October 2000, IEEE, vol. 10, no. 7, pp. 1080-1087.
Although the DCT-based subband decomposition approach provides better efficiency in the spatial scalability mode than the conventional video data processing systems and methods, it still has some disadvantages in processing spatially scalable video data. The disadvantages include the requirement of new quantization matrices for DCT processes. In other words, the DCT-based subband approach creates data whose DCT coefficients are statistically very different from the DCT coefficients of original pixels, and, hence, new quantization matrices for the DCT coefficients must be used to obtain good video quality. The DCT-based subband approach also must be modified to obtain flexibility in varying the relative bit rate allocation between base layer data and enhancement layer data. Thus, an interpolation filter used in the DCT-based subband approach to compute based layer predictions cannot be optimal.